connecting-datacloud
Salesforce Data Cloud Connect phase. Use this skill when the user manages Data Cloud connections, connectors, or sets up a new source system. TRIGGER when: user manages Data Cloud connections, connectors, connector metadata, tests a connection, browses source objects or databases, or sets up a new source system. DO NOT TRIGGER when: the task is about data streams or DLOs (use preparing-datacloud), DMOs or identity resolution (use harmonizing-datacloud), retrieval/search (use retrieving-datacloud), or STDM telemetry (use observing-agentforce).
What this skill does
# connecting-datacloud: Data Cloud Connect Phase Use this skill when the user needs **source connection work**: connector discovery, connection metadata, connection testing, source-object browsing, connector schema inspection, or connector-specific setup payloads for external sources. ## When This Skill Owns the Task Use `connecting-datacloud` when the work involves: - `sf data360 connection *` - connector catalog inspection - connection creation, update, test, or delete - browsing source objects, fields, databases, or schemas - identifying connector types already in use - preparing connector definitions for Snowflake, SharePoint Unstructured, or Ingestion API sources Delegate elsewhere when the user is: - creating data streams or DLOs → [preparing-datacloud](../preparing-datacloud/SKILL.md) - creating DMOs, mappings, IR rulesets, or data graphs → [harmonizing-datacloud](../harmonizing-datacloud/SKILL.md) - writing Data Cloud SQL or search-index workflows → [retrieving-datacloud](../retrieving-datacloud/SKILL.md) --- ## Required Context to Gather First Ask for or infer: - target org alias - connector type or source system - whether the user wants inspection only or live mutation - connection name or ID if one already exists - whether credentials are already configured outside the CLI - whether the user also expects stream creation right after connection setup - whether the source is a database, an unstructured document source, or an Ingestion API feed --- ## Core Operating Rules - Verify the plugin runtime first; see [../orchestrating-datacloud/references/plugin-setup.md](../orchestrating-datacloud/references/plugin-setup.md). - Run the shared readiness classifier before mutating connections: `node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase connect --json`. - Prefer read-only discovery before connection creation. - Suppress linked-plugin warning noise with `2>/dev/null` for standard usage. - Remember that `connection list` requires `--connector-type`. - For `connection test`, pass `--connector-type` when resolving a non-Salesforce connection by name. - Discover existing connector types from streams first when the org is unfamiliar. - Use curated example payloads before inventing connector-specific credentials or parameters. - For connector types outside the curated examples, inspect a known-good UI-created connection via REST before building JSON. - Do not promise API-based stream creation for every connector type just because connection creation succeeds. --- ## Recommended Workflow ### 1. Classify readiness for connect work ```bash node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase connect --json ``` ### 2. Discover connector types ```bash sf data360 connection connector-list -o <org> 2>/dev/null sf data360 data-stream list -o <org> 2>/dev/null ``` ### 3. Inspect connections by type ```bash sf data360 connection list -o <org> --connector-type SalesforceDotCom 2>/dev/null sf data360 connection list -o <org> --connector-type REDSHIFT 2>/dev/null sf data360 connection list -o <org> --connector-type SNOWFLAKE 2>/dev/null ``` ### 4. Inspect a specific connection or uploaded schema ```bash sf data360 connection get -o <org> --name <connection> 2>/dev/null sf data360 connection objects -o <org> --name <connection> 2>/dev/null sf data360 connection fields -o <org> --name <connection> 2>/dev/null sf data360 connection schema-get -o <org> --name <connection-id> 2>/dev/null ``` ### 5. Test or create only after discovery ```bash sf data360 connection test -o <org> --name <connection> --connector-type <type> 2>/dev/null sf data360 connection create -o <org> -f connection.json 2>/dev/null ``` ### 6. Start from curated example payloads for external connectors Use the phase-owned examples before inventing a payload from scratch: - `examples/connections/heroku-postgres.json` - `examples/connections/redshift.json` - `examples/connections/sharepoint-unstructured.json` - `examples/connections/snowflake-connection.json` - `examples/connections/ingest-api-connection.json` - `examples/connections/ingest-api-schema.json` Typical Ingestion API setup flow: ```bash sf data360 connection create -o <org> -f examples/connections/ingest-api-connection.json 2>/dev/null sf data360 connection schema-upsert -o <org> --name <connector-id> -f examples/connections/ingest-api-schema.json 2>/dev/null sf data360 connection schema-get -o <org> --name <connector-id> 2>/dev/null ``` ### 7. Discover payload fields for unknown connector types Create one in the UI, then inspect it directly: ```bash sf api request rest "/services/data/v66.0/ssot/connections/<id>" -o <org> ``` --- ## High-Signal Gotchas - `connection list` has no true global "list all" mode; query by connector type. - The connector catalog name and connection connector type are not always the same label. - `connection test` may need `--connector-type` for name resolution when the source is not a default Salesforce connector. - An empty connection list usually means "enabled but not configured yet", not "feature disabled". - Heroku Postgres, Redshift, Snowflake, SharePoint Unstructured, and Ingestion API all use different credential and parameter shapes; reuse the curated examples instead of guessing. - SharePoint Unstructured uses `clientId`, `clientSecret`, and `tokenEndpoint` in the `credentials` array and does not require a `parameters` array. - Snowflake uses key-pair auth and can often be created through the API, but downstream stream creation can still remain UI-only. - Ingestion API connector setup is incomplete until `connection schema-upsert` has uploaded the object schema. - Some external connector credential setup still depends on UI-side configuration or external-system permissions. --- ## Output Format ```text Connect task: <inspect / create / test / update> Connector type: <SalesforceDotCom / REDSHIFT / SNOWFLAKE / SPUnstructuredDocument / IngestApi / ...> Target org: <alias> Commands: <key commands run> Verification: <passed / partial / blocked> Next step: <prepare phase or connector follow-up> ``` --- ## References - [README.md](README.md) - [examples/connections/heroku-postgres.json](examples/connections/heroku-postgres.json) - [examples/connections/redshift.json](examples/connections/redshift.json) - [examples/connections/sharepoint-unstructured.json](examples/connections/sharepoint-unstructured.json) - [examples/connections/snowflake-connection.json](examples/connections/snowflake-connection.json) - [examples/connections/ingest-api-connection.json](examples/connections/ingest-api-connection.json) - [examples/connections/ingest-api-schema.json](examples/connections/ingest-api-schema.json) - [../orchestrating-datacloud/references/plugin-setup.md](../orchestrating-datacloud/references/plugin-setup.md) - [../orchestrating-datacloud/references/feature-readiness.md](../orchestrating-datacloud/references/feature-readiness.md) - [../orchestrating-datacloud/UPSTREAM.md](../orchestrating-datacloud/UPSTREAM.md)
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